+ All Categories
Home > Documents > Introduction to Geographic Information Systems Spring 2013 (INF 385T-28437) Dr. David Arctur...

Introduction to Geographic Information Systems Spring 2013 (INF 385T-28437) Dr. David Arctur...

Date post: 26-Feb-2016
Category:
Upload: marinel
View: 21 times
Download: 0 times
Share this document with a friend
Description:
Introduction to Geographic Information Systems Spring 2013 (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin Lecture 5 February 7, 2013 Spatial Reference Systems, Data S ources. Outline. Models of the Earth Map projections Coordinate systems - PowerPoint PPT Presentation
74
Introduction to Geographic Information Systems Spring 2013 (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin Lecture 5 February 7, 2013 Spatial Reference Systems, Data Sources
Transcript
Page 1: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Introduction to Geographic Information Systems Spring 2013 (INF 385T-28437)

Dr. David ArcturLecturer, Research Fellow

University of Texas at Austin

Lecture 5February 7, 2013

Spatial Reference Systems, Data Sources

Page 2: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Outline

Models of the Earth Map projections Coordinate systems GIS data sources Vector data formats Raster data formats

2INF385T(28437) – Spring 2013 – Lecture 5

Page 3: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

3

Models of the Earth’s shape

Sphere with radius of ~6378 km Ellipsoid (or Spheroid) with equatorial

radius (semimajor axis) of ~6378 km and polar radius (semiminor axis) of ~6357 km Difference of ~21km usually expressed as

“flattening” (f) ratio of the ellipsoid: f = difference / major axis = ~ 1/300 for

Earth and “inverse flattening” would be ~300

INF385T(28437) – Spring 2013 – Lecture 5

Page 4: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

4

Ellipsoid dimensions and flattening

INF385T(28437) – Spring 2013 – Lecture 5

Ellipsoid = Spheroid in GIS…

Page 5: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Ellipsoid vs Geoid vs Datum

The Geoid is approximately where sea level would be throughout the world (measured by plumb bob away from coastal areas)

Due to variations in the Earth’s gravity field, this “global sea level” would not fit any one ellipsoid, as evident in figure

Datum = shape of ellipsoid AND location of origin for axis of rotation relative to Earth center of mass

Page 6: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

6

Horizontal Control DatumsCommons North American Datums NAD27 (1927 North American Datum)

Clarke (1866) ellipsoid, non-geocentric (local origin) for axis of rotation

NAD83 (1983 North American Datum) GRS80 ellipsoid, geocentric origin for axis of

rotation WGS84 (1984 World Geodetic System)

WGS84 ellipsoid, geocentric, nearly identical to NAD83

Other datums are also in use globallyINF385T(28437) – Spring 2013 – Lecture 5

Page 7: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

7

Datum shifts

INF385T(28437) – Spring 2013 – Lecture 5

Page 8: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

8

Datum transformations Theoretical method: use equations

relating Lat/Lon in one datum to another

Empirical method: use grid of differences to convert values directly from one datum to another

See Esri digital book on Map Projections for more information

INF385T(28437) – Spring 2013 – Lecture 5

Page 9: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

MAP PROJECTIONSHow do we get from 3D Earth to 2D maps???

9INF385T(28437) – Spring 2013 – Lecture 5

Page 10: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Latitude and longitude Longitude (meridians)

10INF385T(28437) – Spring 2013 – Lecture 5

Page 11: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Latitude and longitude Latitude (parallels)

11INF385T(28437) – Spring 2013 – Lecture 5

Page 12: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Latitude and longitude° Longitude (prime meridian)0

° Latitude (equator)0

12INF385T(28437) – Spring 2013 – Lecture 5

Page 13: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Latitude and longitude

Pittsburgh, PA USA

-80

40

Coordinates

13INF385T(28437) – Spring 2013 – Lecture 5

Page 14: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Lat/Long coordinates Degrees, minutes, and seconds (DMS):

40° 26′ 2″ N latitude -80° 0′ 58″ W longitude

Decimal degrees (DD) 1 degree = 60 minutes, 1 minute = 60 seconds 40° 26′ 2″ = 40 + 26/60 + 2/3600 = 40 + .43333 + .00055 = 40.434°

14INF385T(28437) – Spring 2013 – Lecture 5

Page 15: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Lat/long coordinates

Translated to distance World circumference through the poles

is 24,859.82 miles, so for latitude: 1° = 24,859.82 / 360 = 69.1 miles 1′ = 24,859.82 / (360 * 60) = 1.15 miles 1″ = 24,859.82 * 5,280 / (360 * 3,600) =

101 feet Length of the equator is 24,901.55

miles15INF385T(28437) – Spring 2013 – Lecture 5

Page 16: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

16

Picking a projection …[or: how big do you like Greenland?]

INF385T(28437) – Spring 2013 – Lecture 5

Page 17: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

17

Most-used methods

INF385T(28437) – Spring 2013 – Lecture 5

Page 18: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Mercator projection (1569) Conformal projection Cylindrical Parallels and meridians at

right angles Linear scale is constant in

all directions around any point

Preserves angles and shapes of small objects

Distorts the size and shape of large objects

Map projection for nautical purposes

19INF385T(28437) – Spring 2013 – Lecture 5

Page 19: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

INF385T(28437) – Spring 2013 – Lecture 5

Page 20: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Hammer – Aitoff (1882-1889) Equal-area Modified azimuthal

projection Good for population

density (world area) Difficult to see some

areas

21INF385T(28437) – Spring 2013 – Lecture 5

Page 21: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Robinson projection (1961) Pseudocylindrical Neither equal area nor

conformal Meridians curve gently,

avoiding extremes Good compromise

projection for viewing entire world

Used by Rand McNally since the 1960s and by the National Geographic Society (1988 and 1998)

22INF385T(28437) – Spring 2013 – Lecture 5

Page 22: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

INF385T(28437) – Spring 2013 – Lecture 5

Page 23: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Albers Equal Area Conic projection Scale and shape are

not preserved, distortion is minimal between the standard parallels

Standard projection for British Columbia, U.S. Geological Survey, U.S. Census Bureau

24INF385T(28437) – Spring 2013 – Lecture 5

Page 24: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

25

Other map projections…

INF385T(28437) – Spring 2013 – Lecture 5

http://xkcd.com/977/

http://www.watermanpolyhedron.com/maps

Page 25: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

26

And the ever-popular…

INF385T(28437) – Spring 2013 – Lecture 5

Bovine projection(s)

Spilled Coffee

Projection

Page 26: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Projection important for… Measurements used to make important decisions Comparing shapes, areas, distances, or

directions of map features Feature and image themes are aligned

Los Angeles

New York

Los Angeles

New York

Projection: MercatorDistance: 3,124.67 miles

Projection: Albers equal areaDistance: 2,455.03 miles

Actual distance: 2,451 miles 27INF385T(28437) – Spring 2013 – Lecture 5

Page 27: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Projection not important for… Business applications

Not of critical importance Concerned with the relative location of

different features

Large scale maps—street maps Distortion may be negligible Map covers only a small part of the earth’s

surface

28INF385T(28437) – Spring 2013 – Lecture 5

Page 28: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

COORDINATE SYSTEMSLecture 5

29INF385T(28437) – Spring 2013 – Lecture 5

Page 29: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Geographic Coordinate System (GCS)

Spherical coordinates

Angles of rotation of a radius anchored at earth’s center

Latitude and longitude

Census Bureau TIGER files

30INF385T(28437) – Spring 2013 – Lecture 5

Page 30: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

U.S. Census GCS example

31INF385T(28437) – Spring 2013 – Lecture 5

Page 31: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Rectangular coordinate system Used for

locating an intersection on a flat sheet of graph paper or a flat map

Cartesian coordinates (x,y)

State plane and UTM

32INF385T(28437) – Spring 2013 – Lecture 5

Page 32: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

State Plane coordinates Established by the

U.S. Coast and Geodetic Survey in 1930s

Originally North American Datum (NAD 1927)

More recently NAD 1983 and 1983 HARN

Used by local U.S. governments

All positive coordinates in feet (or meters)

33INF385T(28437) – Spring 2013 – Lecture 5

Page 33: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

State Plane zones 125 zones

At least one for each state Cannot have zones joined to make larger

regions Follow state and county

boundaries Each has its own projection:

Lambert conformal projection for zones with east-west extent

Transverse Mercator projection for zones with north-south extent

34INF385T(28437) – Spring 2013 – Lecture 5

Page 34: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

State Plane zones

35INF385T(28437) – Spring 2013 – Lecture 5

Page 35: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

State Plane zones

36INF385T(28437) – Spring 2013 – Lecture 5

Page 36: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Pittsburgh neighborhoods as state plane coordinates

37INF385T(28437) – Spring 2013 – Lecture 5

Page 37: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Universal Transverse Mercator (UTM) Rectangular

coordinate system

Used by U.S. military

Covers entire world

Metric coordinates

Longitude zones are 6° wide

Latitude zones are 8° high

38INF385T(28437) – Spring 2013 – Lecture 5

Page 38: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Coordinate system summary Geographic coordinate system

U.S. Census State plane coordinate system

Local governments U.S. military

Projections defined in ArcCatalog or ArcMap (.prj) files

First file added in a map document sets the projection (others will adjust to it as long as they have a .prj file)

39INF385T(28437) – Spring 2013 – Lecture 5

Page 39: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

GIS DATA SOURCES

We had to go through all that, so we can understand issues around importing spatial data from…

40INF385T(28437) – Spring 2013 – Lecture 5

Page 40: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

GIS data sources ESRI U.S. Census USGS and other government sources GDT Dynamap/2000 U.S. Street Data Engineering companies

land surveys, aerial photos, CAD drawings

University Web sites (e.g. Penn State’s PASDA)

Zillions of others…41INF385T(28437) – Spring 2013 – Lecture 5

Page 41: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

GIS data sources 30+ million Internet search results

type “GIS data download” or “population China .e00

add the name of the state, county, or city to the search

42INF385T(28437) – Spring 2013 – Lecture 5

Page 42: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

GIS departments Web sites Washington, D.C.

dcgis.dc.gov/  Chicago, IL

www.cityofchicago.org/gis

Austin, TX Tip: Search by county name (Travis County,

Texas) http://www.austintexas.gov/development/ ftp://ftp.ci.austin.tx.us/GIS-Data/Regional/coa_gis.html

43INF385T(28437) – Spring 2013 – Lecture 5

Page 43: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

ESRI’s Web site http://

www.esri.com/data/esri_data/demographic-overview

44INF385T(28437) – Spring 2013 – Lecture 5

Page 44: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

U.S. Census Bureau Started building a map infrastructure in

the late 1970s and early 1980s Census mapping needs were twofold:

To assign census employees to areas of responsibility, covering the entire country and its possessions

To report and display census tabulations by area, officials determined that the smallest area needed for these purposes is a city block or its equivalent

45INF385T(28437) – Spring 2013 – Lecture 5

Page 45: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

U.S. Census Bureau Compiles all line features used to

create a block layer for the entire country

Map features smaller than are the responsibility of local governments deeded land parcels buildings street curbs parking lots others?

46INF385T(28437) – Spring 2013 – Lecture 5

Page 46: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Census TIGER/Line files Topologically Integrated Geographic

Encoding and Referencing files Census Bureau’s product for digital

mapping of the U.S. Available for the entire U.S. and its

possessions Include the following geographic features

roads and street centerlines railroads rivers lakes census statistical boundaries

47INF385T(28437) – Spring 2013 – Lecture 5

Page 47: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

48

TIGER census tracts Statistical boundary (below county

level) between 1,000 and 8,000 people (in

general) 1,700 housing units or 4,000 people homogeneous population characteristics

(economic status and living conditions) normally follow visible features may follow governmental unit boundaries

and other nonvisible features more than 60,000 census tracts in Census

2000 Also, the legal basis for developing

congressional districts INF385T(28437) – Spring 2013 – Lecture 5

Page 48: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

PA tracts

49INF385T(28437) – Spring 2013 – Lecture 5

Page 49: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Allegheny County tracts

50INF385T(28437) – Spring 2013 – Lecture 5

Page 50: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Pittsburgh tracts

51INF385T(28437) – Spring 2013 – Lecture 5

Page 51: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

TIGER census block groups

Subdivision of a census tract 400 housing units, with a minimum of 250

and a maximum of 550 housing units Follow clearly visible features such as

roads, rivers, and railroads

52INF385T(28437) – Spring 2013 – Lecture 5

Page 52: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Census block groups

53GIS TUTORIAL 1 - Basic Workbook

Page 53: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

54

TIGER census blocks Smallest geographic area for which the

Census Bureau collects and tabulates decennial census information Visible boundaries

street road stream Shoreline

Nonvisible boundaries county, city, neighborhood boundary property line

54GIS TUTORIAL 1 - Basic WorkbookINF385T(28437) – Spring 2013 – Lecture 5

Page 54: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Census blocks

55GIS TUTORIAL 1 - Basic Workbook

Page 55: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Other TIGER layers

56INF385T(28437) – Spring 2013 – Lecture 5

Page 56: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

U.S. Census Bureau data tables

http://factfinder2.census.gov/

57INF385T(28437) – Spring 2013 – Lecture 5

Page 57: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Summary File (SF1) tables

58GIS TUTORIAL 1 - Basic Workbook

Page 58: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Summary File (SF3) tables

59INF385T(28437) – Spring 2013 – Lecture 5

Page 59: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

SF tables comparisons

SF1 Population Age Sex Race Housing units FFH

SF3 Income Educational

attainment Citizenship Transportation Detailed housing

60INF385T(28437) – Spring 2013 – Lecture 5

Page 60: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Census summary Shapefiles downloaded from

www.census.gov or www.esri.com Data tables downloaded from American

Factfinder http://factfinder2.census.gov Data joins needed to join SF1 or SF3 to

shapefiles

INF385T(28437) – Spring 2013 – Lecture 5 61

Page 61: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

VECTOR DATA FORMATSLecture 5

62INF385T(28437) – Spring 2013 – Lecture 5

Page 62: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

ArcInfo coverages Created using ESRI’s ArcInfo software Older format (import/export as “.e00”) Set of files within a folder or directory called

a workspace Files represent different types of topology or

feature types

63INF385T(28437) – Spring 2013 – Lecture 5

Page 63: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Coverage attribute table Area and perimeter

Coverage_ and Coverage_ID

64INF385T(28437) – Spring 2013 – Lecture 5

Page 64: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

65

Shapefiles ArcView native format

Minimum files .shp–stores feature geometry .shx–stores index of features .dbf–stores attribute data

Additional files .prj–projection data .xml–metadata .sbn and .sbx–store additional indices

INF385T(28437) – Spring 2013 – Lecture 5

Page 65: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

CAD drawings CAD software

Autodesk, AutoCAD (.dwg) Bentley, Microstation (.dgn, .dxf)

Often used by engineering companies Architectural details, instructions to

builders Roads, bridges, dams

Better digitizing precision66INF385T(28437) – Spring 2013 – Lecture 5

Page 66: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

CAD drawings

67INF385T(28437) – Spring 2013 – Lecture 5

Page 67: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

CAD layers

68INF385T(28437) – Spring 2013 – Lecture 5

Page 68: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Event files Data table that includes map coordinates, such as latitude and longitude or projected coordinates

69INF385T(28437) – Spring 2013 – Lecture 5

Page 69: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Event files

70INF385T(28437) – Spring 2013 – Lecture 5

Page 70: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Export event files

71INF385T(28437) – Spring 2013 – Lecture 5

Creates point features

Page 71: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

RASTER DATA FORMATSLecture 5

72INF385T(28437) – Spring 2013 – Lecture 5

Page 72: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Digital file formats TIFF (Tagged Image File Format)

.tif file extension Very high quality images Commonly used in publishing Sizes are large because it is uncompressed

GIF (Graphic Interchange Format): .gif as its file extension. Ideal for schematic drawings that have

relatively large areas with solid color fill and few color variations.

Small file sizes

73INF385T(28437) – Spring 2013 – Lecture 5

Page 73: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

74

Digital file formats JPEG (Joint Photographic Experts

Group): .jpg file extension. Most widely used format for photographs

and other images that have a lot of color variations

Uses file compression at the expense of picture detail, if you specify a lot of compression

INF385T(28437) – Spring 2013 – Lecture 5

Page 74: Introduction to Geographic Information Systems  Spring 2013  (INF 385T-28437) Dr. David Arctur Lecturer, Research Fellow University of Texas at Austin

Summary Models of the Earth Map projections Coordinate systems GIS data sources Vector data formats Raster data formats

75INF385T(28437) – Spring 2013 – Lecture 5


Recommended